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About the Role
Lead the technical direction and delivery of fault detection and fallback systems for driverless operation, working alongside machine learning experts to build robust systems. This role requires a deep systems understanding of robotics for real-world deployment.
Responsibilities
- Set the technical strategy and roadmap for fault detection and fallback from a robotics systems perspective, including behavioral scope, operating envelope, system interfaces, and measurable acceptance criteria.
- Design and train fault detection mechanisms using evidence-based methods to enable robust driverless operation.
- Collaborate across functions and expertise areas with machine learning, inference optimisation, and software engineers.
- Lead integration into the shared driving stack, align technical decisions across teams, and raise the bar through architecture reviews, mentoring, and clear communication of risks, trade-offs, and evidence.
- Use judgement and expertise to improve the overall robustness of the robot system beyond just fault detection and fallback.
Requirements
- Proficiency in developing, implementing, and troubleshooting robotics solutions, backed by practical, real-world experience.
- A track record of staff-level technical leadership: setting direction for ambiguous programmes, aligning multiple teams, and carrying work from research through production deployment.
- Exceptional technical judgement and communication: able to make safety-relevant trade-offs explicit, define the evidence needed for decisions, and lead without relying on formal authority.
- Experience with Python and C++ for robotics.
Skills
- Robotics
- Python
- C++
- Machine Learning
- Inference Optimisation
- Cloud infrastructure for monitoring
- Embedded / real-time systems
Experience Level
- Staff-level
About the Company
- Wayve's AV Core organisation builds foundational capabilities for assisted and automated driving - collision avoidance, model understanding, and robustness under failure.
- The Core Model Safety team is a focused, high-impact senior team with strong ownership, access to large-scale training and fleet data, and close partners in research, simulation, evaluation, and applied engineering.